↓ Skip to main content

Q ST MEETS THE G MATRIX: THE DIMENSIONALITY OF ADAPTIVE DIVERGENCE IN MULTIPLE CORRELATED QUANTITATIVE TRAITS

Overview of attention for article published in Evolution, March 2008
Altmetric Badge

Citations

dimensions_citation
62 Dimensions

Readers on

mendeley
145 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Q ST MEETS THE G MATRIX: THE DIMENSIONALITY OF ADAPTIVE DIVERGENCE IN MULTIPLE CORRELATED QUANTITATIVE TRAITS
Published in
Evolution, March 2008
DOI 10.1111/j.1558-5646.2008.00374.x
Pubmed ID
Authors

Stephen F. Chenoweth, Mark. W. Blows

Abstract

The Q(ST)-F(ST) comparison has become an increasingly common method for inferring adaptive quantitative trait divergence among populations. For cases in which there is divergence in multiple traits, most studies have applied the method by performing multiple univariate Q(ST)-F(ST) comparisons. However, because traits are often genetically correlated, such univariate analyses are likely to paint a simplified picture of adaptive divergence. Here we show how the multivariate analogue of Q(ST), F(STq), which accounts for genetic correlations among traits, can be used to supply a more detailed picture of multitrait divergence. We apply the method to naturally occurring genetic variation for a suite of sexually selected display traits in Drosophila serrata. The analyses suggest the operation of divergent multivariate selection that has influenced multiple independent axes of genetic variance in a sex-specific manner. Finally, we show how a comparison of the components of F(STq), the average within and among population genetic variance-covariance matrices, G(W) and G(B), can be used as an additional test of the null expectation of neutral divergence, and allows for an investigation of whether natural populations have diverged along major or minor axes of genetic variance.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
Finland 2 1%
Germany 2 1%
France 1 <1%
Canada 1 <1%
Romania 1 <1%
Argentina 1 <1%
Japan 1 <1%
Spain 1 <1%
Other 0 0%
Unknown 131 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 55 38%
Student > Ph. D. Student 30 21%
Professor > Associate Professor 18 12%
Professor 11 8%
Other 8 6%
Other 16 11%
Unknown 7 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 114 79%
Biochemistry, Genetics and Molecular Biology 10 7%
Environmental Science 6 4%
Unspecified 2 1%
Earth and Planetary Sciences 1 <1%
Other 2 1%
Unknown 10 7%